In spectral-based ink content measurement, improving the accuracy of the spectral collection system and reducing the algorithm complexity of the ink content measurement model are important aspects of research. This study designs a spectral collection system with an M-type Czerny–Turner optical path structure, uses a third-order polynomial fitting method for calibration analysis, collects the spectral of the standard color card and denoises it through Savitzky–Golay convolution smoothing, and establishes a functional relationship between the spectral and the logarithm of ink content. Uninformative Variable Elimination (UVE) and Competitive Adaptive Reweighting Sampling are used to perform comparative analysis on feature wavelength extraction, and a prediction model for printing ink content is established. Experimental results show that the R2 of ink C, ink M, and ink Y are 0.9981, 0.9975, and 0.9892, respectively, and the root mean square error is 0.0134, 0.0153, and 0.0317, respectively, showing good performance in ink prediction accuracy.